Reading: CNN-CR — CNN for Image Compact-Resolution (HEVC Intra)

VDSR-Like Network, Outperforms EDSR & Li TCSVT’18


1. CNN-CR: Loss Function

CNN-CR: Loss Function
Different Values of λ

With the above loss function, image CR can generate a low-resolution image which can better preserve high frequency components of the original CR, so that when the CR image is upsampled, higher quality is obtained.

2. CNN-CR: Network Architecture

CNN-CR: Network Architecture
Different Network Depths
Different Downsizing
Residual Learning

3. Separate Training & Joint Training

Progressive Training

4. Application Realizations

(a) Frame-level down- and up-sampling coding scheme. (b) Block-level adaptive down- and up-sampling coding scheme

5. Experimental Results

PSNR on Test Sets
PSNR on Test Sets

6. Results for Image Retargeting

CNN-CRJoint is compared to seam carving and bicubic down-sampling, respectively.

7. Results for Image/Video Compression

RD Curves
Hitting Ratios
Computational Complexity Using GPU

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